Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

Background: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. Methodology: We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. Conclusions: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents

Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

BACKGROUND: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. METHODOLOGY: We developed and implemented an optimized mutation profiling platform ("OncoMap") to interrogate approximately 400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. CONCLUSIONS: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of "actionable" cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents

Bridging the age gap in breast cancer. Impacts of omission of breast cancer surgery in older women with oestrogen receptor positive early breast cancer. A risk stratified analysis of survival outcomes and quality of life

Background Age-related breast cancer treatment variance is widespread with many older women having primary endocrine therapy (PET), which may contribute to inferior survival and local control. This propensity-matched study determined if a subgroup of older women may safely be offered PET. Methods Multicentre, prospective, UK, observational cohort study with propensity-matched analysis to determine optimal allocation of surgery plus ET (S+ET) or PET in women aged ≥70 with breast cancer. Data on fitness, frailty, cancer stage, grade, biotype, treatment and quality of life were collected. Propensity-matching (based on age, health status and cancer stage) adjusted for allocation bias when comparing S+ET with PET. Findings A total of 3416 women (median age 77, range 69–102) were recruited from 56 breast units—2854 (88%) had ER+ breast cancer: 2354 had S+ET and 500 PET. Median follow-up was 52 months. Patients treated with PET were older and frailer than patients treated with S+ET. Unmatched overall survival was inferior in the PET group (hazard ratio, (HR) 0.27, 95% confidence interval (CI) 0.23–0.33, P < 0.001). Unmatched breast cancer–specific survival (BCSS) was also inferior in patients treated with PET (HR: 0.41, CI: 0.29–0.58, P < 0.001 for BCSS). In the matched analysis, PET was still associated with an inferior overall survival (HR = 0.72, 95% CI: 0.53–0.98, P = 0.04) but not BCSS (HR = 0.74, 95% CI: 0.40–1.37, P = 0.34) although at 4–5 years subtle divergence of the curves commenced in favor of surgery. Global health status diverged at certain time points between groups but over 24 months was similar when adjusted for baseline variance. Interpretation For the majority of older women with early ER+ breast cancer, surgery is oncologically superior to PET. In less fit, older women, with characteristics similar to the matched cohort of this study (median age 81 with higher comorbidity and functional impairment burdens, the BCSS survival differential disappears at least out to 4–5 year follow-up, suggesting that for those with less than 5-year predicted life-expectancy (>90 years or >85 with comorbidities or frailty) individualised decision making regarding PET versus S+ET may be appropriate and safe to offer. The Age Gap online decision tool may support this decision-making process (https://agegap.shef.ac.uk/). Trial registration number ISRCTN: 46099296

Observational cohort study in older women with early breast cancer: Use of radiation therapy and impact on health-related quality of life and mortality

Background Radiotherapy reduces in-breast recurrence risk in early breast cancer (EBC) in older women. This benefit may be small and should be balanced against treatment effect and holistic patient assessment. This study described treatment patterns according to fitness and impact on health-related quality-of-life (HRQoL). Methods A multicentre, observational study of EBC patients aged ≥ 70 years, undergoing breast-conserving surgery (BCS) or mastectomy, was undertaken. Associations between radiotherapy use, surgery, clinico-pathological parameters, fitness based on geriatric parameters and treatment centre were determined. HRQoL was measured using the European Organisation for the Research and Treatment of Cancer (EORTC) questionnaires. Results In 2013–2018 2811 women in 56 UK study centres underwent surgery with a median follow-up of 52 months. On multivariable analysis, age and tumour risk predicted radiotherapy use. Among healthier patients (based on geriatric assessments) with high-risk tumours, 534/613 (87.1%) having BCS and 185/341 (54.2%) having mastectomy received radiotherapy. In less fit individuals with low-risk tumours undergoing BCS, 149/207 (72.0%) received radiotherapy. Radiotherapy effects on HRQoL domains, including breast symptoms and fatigue were seen, resolving by 18 months. Conclusion Radiotherapy use in EBC patients ≥ 70 years is affected by age and recurrence risk, whereas geriatric parameters have limited impact regardless of type of surgery. There was geographical variation in treatment, with some fit older women with high-risk tumours not receiving radiotherapy, and some older, low-risk, EBC patients receiving radiotherapy after BCS despite evidence of limited benefit. The impact on HRQoL is transient

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse

Improving outcomes for women aged 70 years or above with early breast cancer: research programme including a cluster RCT

Background In breast cancer management, age-related practice variation is widespread, with older women having lower rates of surgery and chemotherapy than younger women, based on the premise of reduced treatment tolerance and benefit. This may contribute to inferior outcomes. There are currently no age- and fitness-stratified guidelines on which to base treatment recommendations. Aim We aimed to optimise treatment choice and outcomes for older women (aged ≥ 70 years) with operable breast cancer. Objectives Our objectives were to (1) determine the age, comorbidity, frailty, disease stage and biology thresholds for endocrine therapy alone versus surgery plus adjuvant endocrine therapy, or adjuvant chemotherapy versus no chemotherapy, for older women with breast cancer; (2) optimise survival outcomes for older women by improving the quality of treatment decision-making; (3) develop and evaluate a decision support intervention to enhance shared decision-making; and (4) determine the degree and causes of treatment variation between UK breast units. Design A prospective cohort study was used to determine age and fitness thresholds for treatment allocation. Mixed-methods research was used to determine the information needs of older women to develop a decision support intervention. A cluster-randomised trial was used to evaluate the impact of this decision support intervention on treatment choices and outcomes. Health economic analysis was used to evaluate the cost–benefit ratio of different treatment strategies according to age and fitness criteria. A mixed-methods study was used to determine the degree and causes of variation in treatment allocation. Main outcome measures The main outcome measures were enhanced age- and fitness-specific decision support leading to improved quality-of-life outcomes in older women (aged ≥ 70 years) with early breast cancer